Dense cellular network deployments relying on the use of massive MIMO technologies are becoming very attractive candidates for emerging and future radio access technologies. This is partly due to the promise of massive MIMO for providing very large throughput increases per base station, due to its ability to harvest large gains in “signal to interference plus noise ratio” (SINR) via “beamforming”, and its ability to multiplex a large number of high-rate streams over each transmission resource element. It is well accepted by now that major gains in the PHY layer in terms of throughput per unit area are to come from the judicious use of dense infrastructure antenna deployments, comprising of a dense network of small cells, possibly equipped with large antenna arrays. Indeed, massive MIMO is very attractive when it is used over dense (small cell) deployments, as in principle it can translate to massive throughput increases per unit area with respect to existing deployments.
Massive MIMO is also envisioned as a candidate for addressing large variations in user load, including effectively serving user-traffic hotspots, such as malls or overcrowded squares. A deployment option that is considered attractive especially for serving user-traffic hotspots involves remote radio-head (RRH) systems in which a base station controls a massive set of antennas that are distributed over many locations. Current proposals for RRH systems consider only one or a few antennas per RRH site. However, with bandwidth expected to become available at higher frequency bands (including the mmWave band), it will become possible to space antenna elements far closer to one another and consider RRHs with a large number of antennas per RRH site. In principle, this would allow the network to simultaneously harvest densification and large-antenna array benefits, thereby delivering large spectral efficiencies per unit area.
Channel state information (CSI) between each base station antenna and the user terminals (UTs) is required to serve multiple streams over the same transmission resources. CSI is obtained by from use of training pilots. A pilot transmitted by one antenna and received by another allows learning the CSI between the two antennas. With massive arrays at the base station side, the preferred option for training, in terms of its training overheads, is to train in the uplink, as one pilot from a user antenna trains all the antennas at nearby base station sites, no matter how many sites and antennas per site. In addition, this immediately makes the user-base station antenna channels available at the base station sites. Note that the channel estimates that become available in this manner at the base station sites can be used for decoding data transmitted in the uplink, and they can also be used to enable multiplexing and beamforming gains for downlink transmission. Indeed, by using UL training and exploiting the uplink-downlink radio channel reciprocity, “Massive MIMO” rates can be achieved in the DL, provided UL training and DL massive MIMO data transmission are within the coherence time and bandwidth of the wireless propagation channel.
Reciprocity-based training can also inherently enable coordinated multipoint (CoMP) transmission, including RRH based transmission. Indeed, a single pilot broadcast from a user antenna trains all the antennas at all nearby base station sites that it can be received at sufficiently high power. It is well known that in cellular networks such CoMP transmission is beneficial for users at the cell edge, i.e., for users that receive equally strong signals from more than one base station. Similar performance gains are expected in RRH systems. Inherently, a user can obtain beamforming gains during the data transmission phase from all the RRH site-antenna combinations that receive the user's pilot broadcast at sufficiently high power.
An important challenge that arises in harvesting densification benefits with cellular networks arises from the fact that UL pilot resources must be reused over the network. It is desirable to make the reuse distance of a pilot resource as small as possible to maximize the densification benefits and the delivered network spectral efficiency and throughput per unit area. Indeed, if the same pilot resource could be effectively reused by two close-by users, then these two close-by users can be served in parallel by the network. However, the users would have to be significantly geographically separated, so that their simultaneously broadcasted pilots are received by their serving base stations at sufficiently high powers and by the other user's base stations at sufficiently low powers. This implies that there is a minimum reuse distance for a users' UL pilot that has to be honored so that users using the same pilot have to be significantly separated to not cause interference to each of the other base stations.
To achieve large cell throughputs and (especially) cell-edge throughputs over well-planned macro-cellular networks with the simplified scheduling and precoding operation, a reuse-7 operation may be used. It is easy to show that in such a massive MIMO network the advocated operation is effectively equivalent to a reuse-1 operation with pilot-reuse 7, whereby the pilots are split into 7 subsets and each subset is reused every 7-th cell.
A pilot reuse extension of this approach over heterogeneous networks having well-planned macro-cells and small cells exists. In particular, pilot dimensions are split between macros and small cells. Furthermore, the individual tier pilot resources are reused with a given pilot reuse factor. For example, the small cell base stations are colored with a finite set of colors, so that no small cell has a same-color neighbor. The pilot reuse factor in this case corresponds to the number of used colors. Although in theory this results in a minimum pilot-reuse of 4 as the minimum number of needed colors is 4, in practice larger number of colors (and thus larger pilot reuse factors to reduce the interference level) are required.
A geographic scheduling approach has been introduced, where in each scheduling slot users at similar locations (relative to their serving cell) are scheduled for transmission across the network. This allows optimizing the precoder, multiplexing gains and the pilot reuse independently per geographic location, i.e., independently for cell-center and cell-edge users. With this operation, substantial gains can be harvested with respect to macro-cellular networks in terms of both cell and cell-edge throughputs (as well as in terms of the number of antennas needed to achieve a certain level of performance). However, this geographic scheduling approach relies on a well-planned macro-cellular network with dense user traffic with geographic scheduling and optimization is possible. As a result, this approach cannot be directly used in unplanned small cell deployments.